The purpose of this study is to investigate the kinematic
characteristics and differences of the snatch barbell trajectory of 53 kg
class female weight lifters. We take the 2014 Taiwan College Cup
players as examples, and tend to make kinematic applications through
the proven weightlifting barbell track system. The competition videos
are taken by consumer camcorder with a tripod which set up at the side
of the lifter. The results will be discussed in three parts, the first part is
various lifting phase, the second part is the compare lifting between
success and unsuccessful, and the third part is to compare the
outstanding player with the general. Conclusion through the barbell
can be used to observe the trajectories of our players lifting the usual
process cannot be observed in the presence of malfunction or habits, so
that the coach can find the problem and guide the players more
accurately. Our system can be applied in practice and competition to
increase the resilience of the lifter on the field.

This study aims at being acquainted with the using the
body fat percentage (%BF) with body Mass Index (BMI) as input
parameters in fuzzy logic decision support system to predict properly
the lifted weight for students at weightlifting class lift according to
his abilities instead of traditional manner. The sample included 53
male students (age = 21.38 ± 0.71 yrs, height (Hgt) = 173.17 ± 5.28
cm, body weight (BW) = 70.34 ± 7.87.6 kg, Body mass index (BMI)
23.42 ± 2.06 kg.m-2, fat mass (FM) = 9.96 ± 3.15 kg and fat
percentage (% BF) = 13.98 ± 3.51 %.) experienced the weightlifting
class as a credit and has variance at BW, Hgt and BMI and FM. BMI
and % BF were taken as input parameters in FUZZY logic whereas
the output parameter was the lifted weight (LW). There were
statistical differences between LW values before and after using
fuzzy logic (Diff 3.55± 2.21, P > 0.001). The percentages of the LW
categories proposed by fuzzy logic were 3.77% of students to lift 1.0
fold of their bodies; 50.94% of students to lift 0.95 fold of their
bodies; 33.96% of students to lift 0.9 fold of their bodies; 3.77% of
students to lift 0.85 fold of their bodies and 7.55% of students to lift
0.8 fold of their bodies. The study concluded that the characteristic
changes in body composition experienced by students when
undergoing weightlifting could be utilized side by side with the
Fuzzy logic decision support system to determine the proper
workloads consistent with the abilities of students.